Web: http://arxiv.org/abs/2201.10395

Jan. 26, 2022, 2:11 a.m. | Ali Ismail, Mariette Awad

cs.LG updates on arXiv.org arxiv.org

In the aftermath of disasters, building damage maps are obtained using change
detection to plan rescue operations. Current convolutional neural network
approaches do not consider the similarities between neighboring buildings for
predicting the damage. We present a novel graph-based building damage detection
solution to capture these relationships. Our proposed model architecture learns
from both local and neighborhood features to predict building damage.
Specifically, we adopt the sample and aggregate graph convolution strategy to
learn aggregation functions that generalize to unseen …

arxiv building cross cv graph networks

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